code: def test_train_model_with_serialization(self):
      # Serializer handles discretization of the data.
      precision = 2
      number_of_time_series = 2
      vocab_size = 16
      srl = space_serializer.BoxSpaceSerializer(
          space=gym.spaces.Box(
              shape=(number_of_time_series,), low=0.0, high=16.0
          ),
          vocab_size=vocab_size,
          precision=precision,
      )
  
      def model(mode):
          del mode
          return serialization_utils.SerializedModel(
              functools.partial(
                  trax_models.TransformerLM,
                  vocab_size=vocab_size,
                  d_model=16,
                  d_ff=8,
                  n_layers=1,
                  n_heads=1,
              ),
              observation_serializer=srl,
              action_serializer=srl,
              significance_decay=0.9,
          )
  
      output_dir = self.create_tempdir().full_path
      state = trainer_lib.train(
          output_dir=output_dir,
          model=model,
          inputs=functools.partial(
              signal_inputs,
              seq_len=5,
              batch_size=64,
              depth=number_of_time_series,
          ),
          steps=2,
      )
      self.assertEqual(2, state.step)
  
imports: import functools
  from absl.testing import absltest
  from absl.testing import parameterized
  import gin
  import gym
  from jax import numpy
  import numpy
  from trax import models
  from trax import shapes
  from trax import test_utils
  from trax.data import inputs
  from trax.layers import base
  from trax.models import transformer
  from trax.rl import serialization_utils
  from trax.rl import space_serializer
  from trax.supervised import trainer_lib
label_desc: Use image node_id 3 for calling the SerializationTest obj's underlying member method code with example usage: obj.test_train_model_with_serialization() and returns: serialization_utils